Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services. One area of development has been customizing services, content, communications (e.g., marketing, advertisements), etc. according to user characteristics to make such services more effective or relevant to the individual user. It is noted that of the many characteristics associated with a user, age is one of the most important distinguishing features for targeting services. A number of services can benefit from knowing a user's age. For example, an advertisement targeted to a properly matched age group can greatly improve the click through rate. However, obtaining age information from users is a significant challenge. Users are often reluctant to provide this information because they may believe it is too personal to give out freely, or users may simply be jaded or tired of providing registration and related information. Accordingly, service providers and device manufacturers face significant technical challenges to enabling accurate and efficient determination of a user's age while reducing or eliminating any data input burden imposed on the user.